The Treeterbi and Parallel Treeterbi algorithms: efficient, optimal decoding for ordinary, generalized and pair HMMs

Motivation: Hidden Markov models (HMMs) and generalized HMMs been successfully applied to many problems, but the standard Viterbi algorithm for computing the most probable interpretation of an input sequence (known as decoding) requires memory proportional to the length of the sequence, which can be...

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Veröffentlicht in:	Bioinformatics Jg. 23; H. 5; S. 545 - 554
Hauptverfasser:	Keibler, Evan, Arumugam, Manimozhiyan, Brent, Michael R.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Oxford University Press 01.03.2007 Oxford Publishing Limited (England)
Schlagworte:	Algorithms Biological and medical sciences Chromosomes Chromosomes, Human Computational Biology DNA, Complementary - chemistry Fundamental and applied biological sciences. Psychology General aspects Genes Genomics - methods Humans Markov Chains Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects) Programming Languages Original document Parallel algorithm Gene Memory Prediction Hidden Markov model Software Web site Bioinformatics Viterbi decoding Comparative study Optimization
ISSN:	1367-4803, 1367-4811, 1367-4811, 1460-2059
Online-Zugang:	Volltext
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